Neural Dynamics of the Primate Attention Network
Sabine Kastner, Professor of Psychology
Princeton Neuroscience Institute, Princeton University
The selection of information from cluttered sensory environments is one of the most fundamental cognitive operations performed by the primate brain. This process engages a large-scale network that consists of multiple nodes, distributed across cortical and subcortical regions. The lecture will focus on temporal dynamics within this network that shape both the sampling of and responses to our environment, with an emphasis on thalamocortical interactions. The lecture will also discuss the importance of comparative electrophysiology and neuroimaging in human and monkey brains.
Sabine Kastner is a Professor of Neuroscience and Psychology at Princeton University. She studies the neural basis of visual perception, attention, and awareness in the healthy, adult primate brain, in patients with brain lesions and during development. Kastner is a Fellow of the American Academy of Arts & Sciences, the American Psychological Society, the Society for Experimental Psychology and a Member of the German National Academy of Sciences (Leopoldina). Kastner is passionate about public outreach such as fostering the careers of young women in science, promoting neuroscience in schools and public education and exploring the intersection of visual neuroscience and art.
Stan Dehaene, Professor Experiential Cognitive Psychology, College De France
Natural language is often seen as the single factor that explains the cognitive singularity of the human species. Instead, we propose that humans possess multiple internal languages of thought, akin to computer languages, which encode and compress structures in various domains (mathematics, music, shape…). These languages rely on cortical circuits distinct from classical language areas. Each is characterized by (1) the discretization of a domain using a small set of symbols, and (2) their recursive composition into mental programs that encode nested repetitions with variations. I will present several tasks of elementary shape or sequence perception in which minimum description length in the proposed languages demonstrably captures human behaviour and brain activity, and where magneto-encephalography tracks the postulated mental structures in real time.
Stanislas Dehaene, PhD, is a French psychologist and cognitive neuroscientist. He holds the Chair of Experimental Cognitive Psychology at the Collége de France in Paris. He directs the NeuroSpin center in Saclay, south of Paris, France’s advanced brain imaging research center. His research investigates the neural bases of human cognitive functions such as reading, calculation and language, with a particular interest for the differences between conscious and non-conscious processing, and for the impact of education on the brain. Prof. Dehaene is a member of six academies and a recipient of the Brain Prize. In 2018, he became the president of the newly created French Scientific Council for Education, which advises the French government on scientific approaches to learning and teaching. He is the author of multiple books including Reading in the Brain: The Science and Evolution of a Human Invention (2009) and How We Learn: Why Brains Learn Better Than Any Machine…For Now (2020), which were translated into more than fifteen languages.
MEG over time: brain function over the years, the lifespan and across disorders
Dr Margot Taylor, Director of Functional Neuroimaging, Hospital for Sick Children and Professor, University of Toronto
Understanding brain functioning across the age spectrum is fundamental to advancing our knowledge on both typical and atypical development. In this presentation, I will review some of our studies using MEG throughout development, determining source, connectivity and oscillatory differences between typical development and children and adults with autism or children born very preterm. The protocols include a range of social-cognitive tasks, such as emotional processing, theory of mind and working memory, which have protracted development normally and show deficits in these clinical populations.
Dr. Taylor is the Director of Functional Neuroimaging and Senior Scientist at the Hospital for Sick Children and Professor in Medical Imaging and Psychology at the University of Toronto. Dr. Taylor‘s research has centred on the neural bases of social-cognitive development using MEG, fMRI and MRI. She and her team assess functional and structural brain correlates of high-level cognitive skills from early childhood into adulthood, in typically developing, autistic and very preterm-born populations. Her current focus is the application of OPMs to investigate emerging neural signatures of autism in toddlers.
Dynamic Brain Networks and Machine Learning in MEG
Prof Mark Woolrich, Professor of Computational Neuroscience, Oxford Centre for Human Brain Activity (OHBA), University of Oxford
The activity of functional brain networks is responsible for the emergence of time-varying cognition and behaviour. In this talk I will describe how machine learning methods can be used to infer the dynamics of large-scale networks at sub-second timescales from MEG data. I will show how these approaches can be used to describe the dynamics of phase locking networks in rest and task, to infer transient spectral events (e.g. beta bursts), and to provide a link between memory replay and the activity of resting state networks. The talk will finish with a look at new deep-learning-based approaches, which are offering exciting new possibilities for the future.
Mark Woolrich is a Professor of Computational Neuroscience at the University of Oxford, Head of Analysis and Associate Director at the Oxford centre for Human Brain Activity (OHBA), and a Group Leader in the Wellcome Centre for Integrative Neuroimaging (WIN). His background is in engineering science and his early research career was in fMRI analysis, through which he became a key contributor to FSL. His research now focuses on the development of new computational methods for analysing neuroimaging data, including functional MRI and MEG/EEG data; allowing novel questions to be asked about the function and dysfunction of the human brain.